AWS Lake Formation vs Databricks comparison

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AWS Lake Formation

Comparison Buyer's Guide

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Executive Summary

We performed a comparison between AWS Lake Formation and Databricks based on real PeerSpot user reviews.

Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed AWS Lake Formation vs. Databricks Report (Updated: July 2025).

AWS Lake Formation vs. Databricks

July 2025

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Helped 867,370 peers since 2012

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

AWS Lake Formation

Ranking in Cloud Data Warehouse

8th

Average Rating

8.0

Reviews Sentiment

5.7

Number of Reviews

Ranking in other categories

No ranking in other categories

Databricks

Ranking in Cloud Data Warehouse

9th

Average Rating

8.2

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Data Science Platforms (1st), Streaming Analytics (1st)

Mindshare comparison

As of September 2025, in the Cloud Data Warehouse category, the mindshare of AWS Lake Formation is 5.7%, up from 5.1% compared to the previous year. The mindshare of Databricks is 8.3%, up from 5.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Warehouse Market Share Distribution
Product	Market Share (%)
AWS Lake Formation	5.7%
Databricks	8.3%
Other	86.0%

Cloud Data Warehouse

Featured Reviews

Ciro Baldim Guerra

Sr Analytics Engineer at Itau Unibanco S.A.

Has improved data governance by enabling clear ownership and structured access across teams

In my company, Itaú, we don't utilize all AWS offerings due to rigorous security measures. We operate approximately six to eight months behind other available services. I'm uncertain if gaps exist because of this limitation, though the system functions effectively for us. AWS Lake Formation offers column-level access control for databases, but we haven't implemented this feature either because it hasn't been approved by our compliance, governance, or security areas. In our current setup, everyone from my business unit uses the same consumer account. When access is requested for a table, everyone using that business unit account receives access. This could present a security concern, though it benefits new team members who automatically receive all necessary access permissions. However, I struggle to identify specific improvements needed in AWS Lake Formation.

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ShubhamSharma7

Data Engineer at a engineering company with 1,001-5,000 employees

Capability to integrate diverse coding languages in a single notebook greatly enhances workflow

Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"In the shortest form, what I appreciated about AWS Lake Formation was that the schema definition and data cataloging were quite good."

"The integration of AWS Lake Formation with the IAM for authentication and authorization is very good; I didn't have any problems in the setup and thought it was simple."

"The main benefits that I have seen from using AWS Lake Formation are related to FinOps because you have control of your data and can track your costs since AWS Lake Formation is integrated into a unique platform, which is AWS Cloud Service."

"AWS Lake Formation significantly improves the structure of the data mesh, making it superior to previous structures we used."

"The LF-Tag system with granular permissions was key to the project as a functionality of AWS Lake Formation."

"There is no doubt that this place exceeded my expectations with its incredible ambiance, attentive service, and mouthwatering menu."

"We use AWS Lake Formation typically for the data warehouse."

"AWS Lake Formation has several valuable features that enhance data management, and one particularly beneficial aspect is how it facilitates better collaboration within data teams."

More AWS Lake Formation pros

"The most valuable feature of Databricks is the integration of the data warehouse and data lake, and the development of the lake house. Additionally, it integrates well with Spark for processing data in production."

"Databricks' most valuable feature is the data transformation through PySpark."

"We are completely satisfied with the ease of connecting to different sources of data or pocket files in the search"

"Databricks provides a consistent interface for data engineers to work with data in a consistent language on a single integrated platform for ingesting, processing, and serving data to the end user."

"The tool helps with data processing and analytics with large-scale data or big data since it is associated with managing data at a large scale."

"I haven't heard about any major stability issues. At this time I feel like it's stable."

"We have the ability to scale, collaborate and do machine learning."

"Having one solution for everything, from data engineering to machine learning, is beneficial since everything comes under one hood."

More Databricks pros

Cons

"If I could improve AWS Lake Formation, I would add more integrations with SageMaker."

"I haven't seen any measurable benefits from using AWS Lake Formation, such as time saving, resource saving, or efficiency improvements."

"In our experience what could be improved are not the support, performance or monitoring, but at a managerial level, the very expensive professional services of AWS. This could be an area of improvement for them. It's too expensive to acquire their support."

"The initial onboarding process is challenging because creating a plan takes a month to a month and a half to build out."

"Lake Formation could enhance its capabilities in audit logs, real-time monitoring, and advanced data governance."

"AWS Lake Formation's pricing could be cheaper."

"For the end-users, it's not as user-friendly as it could be."

"Information about the pricing, cost, and setup cost of the AWS solutions would be beneficial."

More AWS Lake Formation cons

"I would like more integration with SQL for using data in different workspaces."

"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."

"The pricing of Databricks could be cheaper."

"The data visualization for this solution could be improved. They have started to roll out a data visualization tool inside Databricks but it is in the early stages. It's not comparable to a solution like Power BI, Luca, or Tableau."

"Databricks' performance when serving the data to an analytics tool isn't as good as Snowflake's."

"In the future, I would like to see Data Lake support. That is something that I'm looking forward to."

"Pricing is one of the things that could be improved."

"Can be improved by including drag-and-drop features."

More Databricks cons

Pricing and Cost Advice

"AWS Lake Formation is a bit expensive."

"The basic version of this solution is now open-source, so there are no license costs involved. However, there is a charge for any advanced functionality and this can be quite expensive."

"My smallest project is around a hundred euros, and my most expensive is just under a thousand euros a week. That is based on terabytes of data processed each month."

"Databricks is a very expensive solution. Pricing is an area that could definitely be improved. They could provide a lower end compute and probably reduce the price."

"The price is okay. It's competitive."

"The product pricing is moderate."

"Databricks uses a price-per-use model, where you can use as much compute as you need."

"The solution uses a pay-per-use model with an annual subscription fee or package. Typically this solution is used on a cloud platform, such as Azure or AWS, but more people are choosing Azure because the price is more reasonable."

"There are different versions."

More Databricks pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

20%

Computer Software Company

11%

Manufacturing Company

Media Company

Financial Services Firm

17%

Computer Software Company

10%

Manufacturing Company

Healthcare Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

By reviewers
Company Size	Count
Small Business	2
Midsize Enterprise	2
Large Enterprise	15

By reviewers
Company Size	Count
Small Business	25
Midsize Enterprise	12
Large Enterprise	56

Questions from the Community

What do you like most about AWS Lake Formation?

It is seamlessly integrated within the AWS ecosystem, making it straightforward to manage access patterns for AWS-native services.

What is your experience regarding pricing and costs for AWS Lake Formation?

I don't understand much about the pricing of AWS Lake Formation, but I know how to search for the cost of Glue jobs, and I use the calculator in Amazon. I use a tool to preview the cost based on th...

What needs improvement with AWS Lake Formation?

I don't know any features that I would want to see included in the future releases of AWS Lake Formation. Making queries in SQL is a reality now, and in the future, it would be beneficial if AWS im...

Which do you prefer - Databricks or Azure Machine Learning Studio?

Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...

How would you compare Databricks vs Amazon SageMaker?

We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...

Which would you choose - Databricks or Azure Stream Analytics?

Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...

Snowflake vs AWS Lake Formation

Comparisons

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Azure Data Factory vs AWS Lake Formation

Compared 20% of the time

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BigQuery vs AWS Lake Formation

Compared 11% of the time

Microsoft Azure Synapse Analytics vs AWS Lake Formation

Compared 7% of the time

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Compared 9% of the time

Microsoft Power BI vs Databricks

Compared 9% of the time

Informatica PowerCenter vs Databricks

Compared 7% of the time

Dremio vs Databricks

Compared 6% of the time

Tableau Enterprise vs Databricks

Compared 5% of the time

More Databricks Competitors

Product Reports

Download AWS Lake Formation product report

AWS Lake Formation

September 2025

Download Databricks product report

September 2025

Also Known As

No data available

Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash

Overview

AWS Lake Formation is a service that makes it easy to set up a secure data lake in days. A data lake is a centralized, curated, and secured repository that stores all your data, both in its original form and prepared for analysis.

Amazon Web Services (AWS)

Databricks is utilized for advanced analytics, big data processing, machine learning models, ETL operations, data engineering, streaming analytics, and integrating multiple data sources.

Organizations leverage Databricks for predictive analysis, data pipelines, data science, and unifying data architectures. It is also used for consulting projects, financial reporting, and creating APIs. Industries like insurance, retail, manufacturing, and pharmaceuticals use Databricks for data management and analytics due to its user-friendly interface, built-in machine learning libraries, support for multiple programming languages, scalability, and fast processing.

What are the key features of Databricks?

User-friendly interface: Simplifies operations and usability.
Built-in machine learning libraries: Facilitates machine learning tasks.
Support for multiple programming languages: Enhances flexibility.
Scalability: Efficiently handles growing data needs.
Fast processing: Improves performance and speed.
Automated optimization: Reduces manual efforts.
Data visualization: Provides insightful visuals.
Collaborative features: Enhances teamwork.
Delta Lake performance: Boosts data management.
Seamless cluster management: Simplifies system operations.

What are the benefits or ROI to look for in Databricks reviews?

Efficiency in handling large datasets: Ensures smooth processing.
Interactive workspace environment: Improves user collaboration.
Integration with platforms: Provides connectivity benefits.
Performance optimization: Enhances overall system performance.
Support for data governance and security: Ensures data integrity and protection.

Databricks is implemented in insurance for risk analysis and claims processing; in retail for customer analytics and inventory management; in manufacturing for predictive maintenance and supply chain optimization; and in pharmaceuticals for drug discovery and patient data analysis. Users value its scalability, machine learning support, collaboration tools, and Delta Lake performance but seek improvements in visualization, pricing, and integration with BI tools.

Sample Customers

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday

Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware